most citedSemantic XAI for contextualized demand forecasting explanations

4 citations · 4 across the 1 of their papers we have counts for

collaborators

5 papers

cs.AI2021

STARdom: an architecture for trusted and secure human-centered manufacturing systems

Jože M. Rožanec, Patrik Zajec, Klemen Kenda +14

There is a lack of a single architecture specification that addresses the needs of trusted and secure Artificial Intelligence systems with humans in the loop, such as human-centere…

cs.AI20214 cited

Semantic XAI for contextualized demand forecasting explanations

Jože M. Rožanec, Dunja Mladenić

The paper proposes a novel architecture for explainable AI based on semantic technologies and AI. We tailor the architecture for the domain of demand forecasting and validate it on…

cs.AI2021

Towards Active Learning Based Smart Assistant for Manufacturing

Patrik Zajec, Jože M. Rožanec, Inna Novalija +3

A general approach for building a smart assistant that guides a user from a forecast generated by a machine learning model through a sequence of decision-making steps is presented.…

cs.LG2021

Reframing demand forecasting: a two-fold approach for lumpy and intermittent demand

Jože M. Rožanec, Dunja Mladenić

Demand forecasting is a crucial component of demand management. While shortening the forecasting horizon allows for more recent data and less uncertainty, this frequently means low…

cs.AI2021

Actionable Cognitive Twins for Decision Making in Manufacturing

Jože M. Rožanec, Jinzhi Lu, Jan Rupnik +5

Actionable Cognitive Twins are the next generation Digital Twins enhanced with cognitive capabilities through a knowledge graph and artificial intelligence models that provide insi…